Open Targets Genetics: systematic identification of trait-associated genes using large-scale genetics and functional genomics

Maya Ghoussaini(Wellcome Sanger Institute), Edward Mountjoy(Wellcome Sanger Institute), Miguel Carmona(European Bioinformatics Institute), Gareth Peat(European Bioinformatics Institute), Ellen M. Schmidt(Wellcome Sanger Institute), Andrew Hercules(European Bioinformatics Institute), Luca Fumis(European Bioinformatics Institute), Alfredo Miranda(European Bioinformatics Institute), Denise Carvalho‐Silva(European Bioinformatics Institute), Annalisa Buniello(European Bioinformatics Institute), Tony Burdett(European Bioinformatics Institute), James Hayhurst(European Bioinformatics Institute), Jarrod Baker(European Bioinformatics Institute), Javier Ferrer(European Bioinformatics Institute), Asier Gonzalez‐Uriarte(European Bioinformatics Institute), Simon Jupp(European Bioinformatics Institute), Mohd Anisul Karim(Wellcome Sanger Institute), Gautier Koscielny(GlaxoSmithKline (United Kingdom)), Sandra Machlitt‐Northen(GlaxoSmithKline (United Kingdom)), Claudio Malangone(European Bioinformatics Institute), Zoë May Pendlington(European Bioinformatics Institute), Paola Roncaglia(European Bioinformatics Institute), Dániel Süveges(European Bioinformatics Institute), Daniel J. Wright(Wellcome Sanger Institute), Olga Vrousgou(European Bioinformatics Institute), Eliseo Papa(Biogen (United States)), Helen Parkinson(European Bioinformatics Institute), Jacqueline A. L. MacArthur(European Bioinformatics Institute), John A. Todd(Centre for Human Genetics), Jeffrey C. Barrett(Wellcome Sanger Institute), Jeremy Schwartzentruber(Wellcome Sanger Institute), David G. Hulcoop(GlaxoSmithKline (United Kingdom)), David Ochoa(European Bioinformatics Institute), Ellen M. McDonagh(European Bioinformatics Institute), Ian Dunham(European Bioinformatics Institute)
Nucleic Acids Research
September 17, 2020
Cited by 692Open Access
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Abstract

Open Targets Genetics (https://genetics.opentargets.org) is an open-access integrative resource that aggregates human GWAS and functional genomics data including gene expression, protein abundance, chromatin interaction and conformation data from a wide range of cell types and tissues to make robust connections between GWAS-associated loci, variants and likely causal genes. This enables systematic identification and prioritisation of likely causal variants and genes across all published trait-associated loci. In this paper, we describe the public resources we aggregate, the technology and analyses we use, and the functionality that the portal offers. Open Targets Genetics can be searched by variant, gene or study/phenotype. It offers tools that enable users to prioritise causal variants and genes at disease-associated loci and access systematic cross-disease and disease-molecular trait colocalization analysis across 92 cell types and tissues including the eQTL Catalogue. Data visualizations such as Manhattan-like plots, regional plots, credible sets overlap between studies and PheWAS plots enable users to explore GWAS signals in depth. The integrated data is made available through the web portal, for bulk download and via a GraphQL API, and the software is open source. Applications of this integrated data include identification of novel targets for drug discovery and drug repurposing.


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